I'm analizing the Argentina stock market (merv)
I download the data from yahoo
library(tseries)
Argentina <- get.hist.quote(instrument="^MERV","1996-10-08","2003-11-03",
quote="Close")
merv <- na.remove(log(Argentina))
I made the Augmented Dickey-Fuller test to analyse
if merv have unit root:
adf.test(merv,k=13)
Dickey-Fuller = -1.4645, p-value = 0.805,
merv have unit root than diff(merv,1) is stationary.
Than I made Breushch-Pagan test to test if residuals are identically distributed:
library(lmtest)
bptest(merv[2:1730]~-1+merv[1:1729],~merv[1:1729]+I(merv[1:1729])^2)
BP = 81.3443, df = 2, p-value = < 2.2e-16
So merv.reg$resid aren't identically distributed. Than merv is heteroscedastik.
Finally I made Box-Ljung test to test if residuals are independently distributed:
(H0: merv.reg$resid are independently distributed)
library(ts)
merv.reg <- lm(merv[2:1730]~-1+merv[1:1729])
Box.test(merv.reg$resid, lag=25,type="Ljung")
X-squared = 54.339, df = 25, p-value = 0.0006004
So, there is evidence to not reject the null hypothesis,
than the residuals are independently distributed.
Because the residuals are not independently distributed, we know that the
squares of residuals are correlated:
cov[(residuals_t)^2, (residuals_(t-k))^2] <> 0 (not zero for k <> 0)
But, the residuals could be uncorrelated, (even when they
are not independent distributed):
cov[residuals_t, residual_(t-k)]=0 !
How can I test that merv.reg$residuals are uncorrelated ?
Thanks a lot.
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